
(FPCore (k n) :precision binary64 (* (/ 1.0 (sqrt k)) (pow (* (* 2.0 PI) n) (/ (- 1.0 k) 2.0))))
double code(double k, double n) {
return (1.0 / sqrt(k)) * pow(((2.0 * ((double) M_PI)) * n), ((1.0 - k) / 2.0));
}
public static double code(double k, double n) {
return (1.0 / Math.sqrt(k)) * Math.pow(((2.0 * Math.PI) * n), ((1.0 - k) / 2.0));
}
def code(k, n): return (1.0 / math.sqrt(k)) * math.pow(((2.0 * math.pi) * n), ((1.0 - k) / 2.0))
function code(k, n) return Float64(Float64(1.0 / sqrt(k)) * (Float64(Float64(2.0 * pi) * n) ^ Float64(Float64(1.0 - k) / 2.0))) end
function tmp = code(k, n) tmp = (1.0 / sqrt(k)) * (((2.0 * pi) * n) ^ ((1.0 - k) / 2.0)); end
code[k_, n_] := N[(N[(1.0 / N[Sqrt[k], $MachinePrecision]), $MachinePrecision] * N[Power[N[(N[(2.0 * Pi), $MachinePrecision] * n), $MachinePrecision], N[(N[(1.0 - k), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 10 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (k n) :precision binary64 (* (/ 1.0 (sqrt k)) (pow (* (* 2.0 PI) n) (/ (- 1.0 k) 2.0))))
double code(double k, double n) {
return (1.0 / sqrt(k)) * pow(((2.0 * ((double) M_PI)) * n), ((1.0 - k) / 2.0));
}
public static double code(double k, double n) {
return (1.0 / Math.sqrt(k)) * Math.pow(((2.0 * Math.PI) * n), ((1.0 - k) / 2.0));
}
def code(k, n): return (1.0 / math.sqrt(k)) * math.pow(((2.0 * math.pi) * n), ((1.0 - k) / 2.0))
function code(k, n) return Float64(Float64(1.0 / sqrt(k)) * (Float64(Float64(2.0 * pi) * n) ^ Float64(Float64(1.0 - k) / 2.0))) end
function tmp = code(k, n) tmp = (1.0 / sqrt(k)) * (((2.0 * pi) * n) ^ ((1.0 - k) / 2.0)); end
code[k_, n_] := N[(N[(1.0 / N[Sqrt[k], $MachinePrecision]), $MachinePrecision] * N[Power[N[(N[(2.0 * Pi), $MachinePrecision] * n), $MachinePrecision], N[(N[(1.0 - k), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{1}{\sqrt{k}} \cdot {\left(\left(2 \cdot \pi\right) \cdot n\right)}^{\left(\frac{1 - k}{2}\right)}
\end{array}
(FPCore (k n) :precision binary64 (if (<= k 1.3e-33) (* (sqrt (/ PI k)) (sqrt (* 2.0 n))) (pow (* k (pow (* PI (* 2.0 n)) (+ k -1.0))) -0.5)))
double code(double k, double n) {
double tmp;
if (k <= 1.3e-33) {
tmp = sqrt((((double) M_PI) / k)) * sqrt((2.0 * n));
} else {
tmp = pow((k * pow((((double) M_PI) * (2.0 * n)), (k + -1.0))), -0.5);
}
return tmp;
}
public static double code(double k, double n) {
double tmp;
if (k <= 1.3e-33) {
tmp = Math.sqrt((Math.PI / k)) * Math.sqrt((2.0 * n));
} else {
tmp = Math.pow((k * Math.pow((Math.PI * (2.0 * n)), (k + -1.0))), -0.5);
}
return tmp;
}
def code(k, n): tmp = 0 if k <= 1.3e-33: tmp = math.sqrt((math.pi / k)) * math.sqrt((2.0 * n)) else: tmp = math.pow((k * math.pow((math.pi * (2.0 * n)), (k + -1.0))), -0.5) return tmp
function code(k, n) tmp = 0.0 if (k <= 1.3e-33) tmp = Float64(sqrt(Float64(pi / k)) * sqrt(Float64(2.0 * n))); else tmp = Float64(k * (Float64(pi * Float64(2.0 * n)) ^ Float64(k + -1.0))) ^ -0.5; end return tmp end
function tmp_2 = code(k, n) tmp = 0.0; if (k <= 1.3e-33) tmp = sqrt((pi / k)) * sqrt((2.0 * n)); else tmp = (k * ((pi * (2.0 * n)) ^ (k + -1.0))) ^ -0.5; end tmp_2 = tmp; end
code[k_, n_] := If[LessEqual[k, 1.3e-33], N[(N[Sqrt[N[(Pi / k), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(2.0 * n), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[Power[N[(k * N[Power[N[(Pi * N[(2.0 * n), $MachinePrecision]), $MachinePrecision], N[(k + -1.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], -0.5], $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;k \leq 1.3 \cdot 10^{-33}:\\
\;\;\;\;\sqrt{\frac{\pi}{k}} \cdot \sqrt{2 \cdot n}\\
\mathbf{else}:\\
\;\;\;\;{\left(k \cdot {\left(\pi \cdot \left(2 \cdot n\right)\right)}^{\left(k + -1\right)}\right)}^{-0.5}\\
\end{array}
\end{array}
if k < 1.29999999999999997e-33Initial program 98.4%
Taylor expanded in k around 0 78.2%
*-commutative78.2%
associate-/l*78.2%
Simplified78.2%
sqrt-unprod78.5%
clear-num78.5%
un-div-inv78.5%
Applied egg-rr78.5%
*-commutative78.5%
sqrt-prod78.2%
div-inv78.3%
clear-num78.2%
sqrt-prod99.2%
*-commutative99.2%
associate-*l*99.3%
sqrt-prod99.5%
Applied egg-rr99.5%
if 1.29999999999999997e-33 < k Initial program 99.6%
associate-*l/99.6%
*-un-lft-identity99.6%
associate-*r*99.6%
div-sub99.6%
metadata-eval99.6%
pow-div100.0%
pow1/2100.0%
associate-/l/99.9%
div-inv99.9%
metadata-eval99.9%
Applied egg-rr99.9%
*-lft-identity99.9%
times-frac99.9%
associate-*l/100.0%
*-lft-identity100.0%
*-commutative100.0%
*-commutative100.0%
Simplified100.0%
associate-/l/99.9%
div-inv99.9%
associate-*r*99.9%
pow1/299.9%
pow-unpow99.9%
pow-prod-down99.9%
associate-*r*99.9%
Applied egg-rr99.9%
associate-*r/99.9%
*-rgt-identity99.9%
*-commutative99.9%
*-commutative99.9%
unpow1/299.9%
*-commutative99.9%
*-commutative99.9%
Simplified99.9%
clear-num99.9%
inv-pow99.9%
sqrt-undiv99.9%
Applied egg-rr99.9%
unpow-199.9%
associate-/l*99.9%
Simplified99.9%
inv-pow99.9%
sqrt-pow2100.0%
pow1100.0%
pow-div99.7%
metadata-eval99.7%
Applied egg-rr99.7%
Final simplification99.6%
(FPCore (k n) :precision binary64 (let* ((t_0 (* 2.0 (* n PI)))) (/ (/ (sqrt t_0) (pow t_0 (* k 0.5))) (sqrt k))))
double code(double k, double n) {
double t_0 = 2.0 * (n * ((double) M_PI));
return (sqrt(t_0) / pow(t_0, (k * 0.5))) / sqrt(k);
}
public static double code(double k, double n) {
double t_0 = 2.0 * (n * Math.PI);
return (Math.sqrt(t_0) / Math.pow(t_0, (k * 0.5))) / Math.sqrt(k);
}
def code(k, n): t_0 = 2.0 * (n * math.pi) return (math.sqrt(t_0) / math.pow(t_0, (k * 0.5))) / math.sqrt(k)
function code(k, n) t_0 = Float64(2.0 * Float64(n * pi)) return Float64(Float64(sqrt(t_0) / (t_0 ^ Float64(k * 0.5))) / sqrt(k)) end
function tmp = code(k, n) t_0 = 2.0 * (n * pi); tmp = (sqrt(t_0) / (t_0 ^ (k * 0.5))) / sqrt(k); end
code[k_, n_] := Block[{t$95$0 = N[(2.0 * N[(n * Pi), $MachinePrecision]), $MachinePrecision]}, N[(N[(N[Sqrt[t$95$0], $MachinePrecision] / N[Power[t$95$0, N[(k * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := 2 \cdot \left(n \cdot \pi\right)\\
\frac{\frac{\sqrt{t\_0}}{{t\_0}^{\left(k \cdot 0.5\right)}}}{\sqrt{k}}
\end{array}
\end{array}
Initial program 99.1%
associate-*l/99.2%
*-un-lft-identity99.2%
associate-*r*99.2%
div-sub99.2%
metadata-eval99.2%
pow-div99.3%
pow1/299.3%
associate-/l/99.3%
div-inv99.3%
metadata-eval99.3%
Applied egg-rr99.3%
*-lft-identity99.3%
times-frac99.2%
associate-*l/99.3%
*-lft-identity99.3%
*-commutative99.3%
*-commutative99.3%
Simplified99.3%
(FPCore (k n) :precision binary64 (let* ((t_0 (* PI (* 2.0 n)))) (/ (sqrt t_0) (sqrt (* k (pow t_0 k))))))
double code(double k, double n) {
double t_0 = ((double) M_PI) * (2.0 * n);
return sqrt(t_0) / sqrt((k * pow(t_0, k)));
}
public static double code(double k, double n) {
double t_0 = Math.PI * (2.0 * n);
return Math.sqrt(t_0) / Math.sqrt((k * Math.pow(t_0, k)));
}
def code(k, n): t_0 = math.pi * (2.0 * n) return math.sqrt(t_0) / math.sqrt((k * math.pow(t_0, k)))
function code(k, n) t_0 = Float64(pi * Float64(2.0 * n)) return Float64(sqrt(t_0) / sqrt(Float64(k * (t_0 ^ k)))) end
function tmp = code(k, n) t_0 = pi * (2.0 * n); tmp = sqrt(t_0) / sqrt((k * (t_0 ^ k))); end
code[k_, n_] := Block[{t$95$0 = N[(Pi * N[(2.0 * n), $MachinePrecision]), $MachinePrecision]}, N[(N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(k * N[Power[t$95$0, k], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \pi \cdot \left(2 \cdot n\right)\\
\frac{\sqrt{t\_0}}{\sqrt{k \cdot {t\_0}^{k}}}
\end{array}
\end{array}
Initial program 99.1%
associate-*l/99.2%
*-un-lft-identity99.2%
associate-*r*99.2%
div-sub99.2%
metadata-eval99.2%
pow-div99.3%
pow1/299.3%
associate-/l/99.3%
div-inv99.3%
metadata-eval99.3%
Applied egg-rr99.3%
*-lft-identity99.3%
times-frac99.2%
associate-*l/99.3%
*-lft-identity99.3%
*-commutative99.3%
*-commutative99.3%
Simplified99.3%
associate-/l/99.3%
div-inv99.2%
associate-*r*99.2%
pow1/299.2%
pow-unpow99.2%
pow-prod-down99.2%
associate-*r*99.2%
Applied egg-rr99.2%
associate-*r/99.3%
*-rgt-identity99.3%
*-commutative99.3%
*-commutative99.3%
unpow1/299.3%
*-commutative99.3%
*-commutative99.3%
Simplified99.3%
Final simplification99.3%
(FPCore (k n) :precision binary64 (if (<= k 4.6e-34) (* (sqrt (/ PI k)) (sqrt (* 2.0 n))) (sqrt (/ (pow (* 2.0 (* n PI)) (- 1.0 k)) k))))
double code(double k, double n) {
double tmp;
if (k <= 4.6e-34) {
tmp = sqrt((((double) M_PI) / k)) * sqrt((2.0 * n));
} else {
tmp = sqrt((pow((2.0 * (n * ((double) M_PI))), (1.0 - k)) / k));
}
return tmp;
}
public static double code(double k, double n) {
double tmp;
if (k <= 4.6e-34) {
tmp = Math.sqrt((Math.PI / k)) * Math.sqrt((2.0 * n));
} else {
tmp = Math.sqrt((Math.pow((2.0 * (n * Math.PI)), (1.0 - k)) / k));
}
return tmp;
}
def code(k, n): tmp = 0 if k <= 4.6e-34: tmp = math.sqrt((math.pi / k)) * math.sqrt((2.0 * n)) else: tmp = math.sqrt((math.pow((2.0 * (n * math.pi)), (1.0 - k)) / k)) return tmp
function code(k, n) tmp = 0.0 if (k <= 4.6e-34) tmp = Float64(sqrt(Float64(pi / k)) * sqrt(Float64(2.0 * n))); else tmp = sqrt(Float64((Float64(2.0 * Float64(n * pi)) ^ Float64(1.0 - k)) / k)); end return tmp end
function tmp_2 = code(k, n) tmp = 0.0; if (k <= 4.6e-34) tmp = sqrt((pi / k)) * sqrt((2.0 * n)); else tmp = sqrt((((2.0 * (n * pi)) ^ (1.0 - k)) / k)); end tmp_2 = tmp; end
code[k_, n_] := If[LessEqual[k, 4.6e-34], N[(N[Sqrt[N[(Pi / k), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(2.0 * n), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[Sqrt[N[(N[Power[N[(2.0 * N[(n * Pi), $MachinePrecision]), $MachinePrecision], N[(1.0 - k), $MachinePrecision]], $MachinePrecision] / k), $MachinePrecision]], $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;k \leq 4.6 \cdot 10^{-34}:\\
\;\;\;\;\sqrt{\frac{\pi}{k}} \cdot \sqrt{2 \cdot n}\\
\mathbf{else}:\\
\;\;\;\;\sqrt{\frac{{\left(2 \cdot \left(n \cdot \pi\right)\right)}^{\left(1 - k\right)}}{k}}\\
\end{array}
\end{array}
if k < 4.60000000000000022e-34Initial program 98.4%
Taylor expanded in k around 0 78.2%
*-commutative78.2%
associate-/l*78.2%
Simplified78.2%
sqrt-unprod78.5%
clear-num78.5%
un-div-inv78.5%
Applied egg-rr78.5%
*-commutative78.5%
sqrt-prod78.2%
div-inv78.3%
clear-num78.2%
sqrt-prod99.2%
*-commutative99.2%
associate-*l*99.3%
sqrt-prod99.5%
Applied egg-rr99.5%
if 4.60000000000000022e-34 < k Initial program 99.6%
Applied egg-rr99.6%
distribute-rgt-in99.6%
metadata-eval99.6%
associate-*l*99.6%
metadata-eval99.6%
*-commutative99.6%
neg-mul-199.6%
sub-neg99.6%
*-commutative99.6%
Simplified99.6%
Final simplification99.6%
(FPCore (k n) :precision binary64 (/ (pow (* 2.0 (* n PI)) (- 0.5 (/ k 2.0))) (sqrt k)))
double code(double k, double n) {
return pow((2.0 * (n * ((double) M_PI))), (0.5 - (k / 2.0))) / sqrt(k);
}
public static double code(double k, double n) {
return Math.pow((2.0 * (n * Math.PI)), (0.5 - (k / 2.0))) / Math.sqrt(k);
}
def code(k, n): return math.pow((2.0 * (n * math.pi)), (0.5 - (k / 2.0))) / math.sqrt(k)
function code(k, n) return Float64((Float64(2.0 * Float64(n * pi)) ^ Float64(0.5 - Float64(k / 2.0))) / sqrt(k)) end
function tmp = code(k, n) tmp = ((2.0 * (n * pi)) ^ (0.5 - (k / 2.0))) / sqrt(k); end
code[k_, n_] := N[(N[Power[N[(2.0 * N[(n * Pi), $MachinePrecision]), $MachinePrecision], N[(0.5 - N[(k / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[k], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\frac{{\left(2 \cdot \left(n \cdot \pi\right)\right)}^{\left(0.5 - \frac{k}{2}\right)}}{\sqrt{k}}
\end{array}
Initial program 99.1%
associate-*l/99.2%
*-lft-identity99.2%
associate-*l*99.2%
div-sub99.2%
metadata-eval99.2%
Simplified99.2%
Final simplification99.2%
(FPCore (k n) :precision binary64 (* (sqrt (/ PI k)) (sqrt (* 2.0 n))))
double code(double k, double n) {
return sqrt((((double) M_PI) / k)) * sqrt((2.0 * n));
}
public static double code(double k, double n) {
return Math.sqrt((Math.PI / k)) * Math.sqrt((2.0 * n));
}
def code(k, n): return math.sqrt((math.pi / k)) * math.sqrt((2.0 * n))
function code(k, n) return Float64(sqrt(Float64(pi / k)) * sqrt(Float64(2.0 * n))) end
function tmp = code(k, n) tmp = sqrt((pi / k)) * sqrt((2.0 * n)); end
code[k_, n_] := N[(N[Sqrt[N[(Pi / k), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(2.0 * n), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{\frac{\pi}{k}} \cdot \sqrt{2 \cdot n}
\end{array}
Initial program 99.1%
Taylor expanded in k around 0 40.8%
*-commutative40.8%
associate-/l*40.8%
Simplified40.8%
sqrt-unprod41.0%
clear-num40.9%
un-div-inv41.0%
Applied egg-rr41.0%
*-commutative41.0%
sqrt-prod40.8%
div-inv40.8%
clear-num40.8%
sqrt-prod50.0%
*-commutative50.0%
associate-*l*50.0%
sqrt-prod50.1%
Applied egg-rr50.1%
Final simplification50.1%
(FPCore (k n) :precision binary64 (* (sqrt n) (sqrt (* PI (/ 2.0 k)))))
double code(double k, double n) {
return sqrt(n) * sqrt((((double) M_PI) * (2.0 / k)));
}
public static double code(double k, double n) {
return Math.sqrt(n) * Math.sqrt((Math.PI * (2.0 / k)));
}
def code(k, n): return math.sqrt(n) * math.sqrt((math.pi * (2.0 / k)))
function code(k, n) return Float64(sqrt(n) * sqrt(Float64(pi * Float64(2.0 / k)))) end
function tmp = code(k, n) tmp = sqrt(n) * sqrt((pi * (2.0 / k))); end
code[k_, n_] := N[(N[Sqrt[n], $MachinePrecision] * N[Sqrt[N[(Pi * N[(2.0 / k), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\sqrt{n} \cdot \sqrt{\pi \cdot \frac{2}{k}}
\end{array}
Initial program 99.1%
Taylor expanded in k around 0 40.8%
*-commutative40.8%
associate-/l*40.8%
Simplified40.8%
sqrt-unprod41.0%
clear-num40.9%
un-div-inv41.0%
Applied egg-rr41.0%
*-commutative41.0%
sqrt-prod40.8%
div-inv40.8%
clear-num40.8%
sqrt-prod50.0%
associate-*l*50.0%
*-commutative50.0%
sqrt-unprod50.0%
Applied egg-rr50.0%
associate-*r/50.0%
*-commutative50.0%
associate-/l*50.0%
Simplified50.0%
(FPCore (k n) :precision binary64 (pow (/ (/ k PI) (* 2.0 n)) -0.5))
double code(double k, double n) {
return pow(((k / ((double) M_PI)) / (2.0 * n)), -0.5);
}
public static double code(double k, double n) {
return Math.pow(((k / Math.PI) / (2.0 * n)), -0.5);
}
def code(k, n): return math.pow(((k / math.pi) / (2.0 * n)), -0.5)
function code(k, n) return Float64(Float64(k / pi) / Float64(2.0 * n)) ^ -0.5 end
function tmp = code(k, n) tmp = ((k / pi) / (2.0 * n)) ^ -0.5; end
code[k_, n_] := N[Power[N[(N[(k / Pi), $MachinePrecision] / N[(2.0 * n), $MachinePrecision]), $MachinePrecision], -0.5], $MachinePrecision]
\begin{array}{l}
\\
{\left(\frac{\frac{k}{\pi}}{2 \cdot n}\right)}^{-0.5}
\end{array}
Initial program 99.1%
Taylor expanded in k around 0 40.8%
*-commutative40.8%
associate-/l*40.8%
Simplified40.8%
sqrt-unprod41.0%
clear-num40.9%
un-div-inv41.0%
Applied egg-rr41.0%
associate-/r/40.9%
associate-*l/40.9%
associate-/l*40.9%
associate-*l*40.9%
sqrt-undiv49.7%
clear-num49.6%
inv-pow49.6%
sqrt-undiv41.5%
sqrt-pow241.5%
*-commutative41.5%
*-commutative41.5%
associate-/r*41.6%
metadata-eval41.6%
Applied egg-rr41.6%
Final simplification41.6%
(FPCore (k n) :precision binary64 (sqrt (* 2.0 (/ n (/ k PI)))))
double code(double k, double n) {
return sqrt((2.0 * (n / (k / ((double) M_PI)))));
}
public static double code(double k, double n) {
return Math.sqrt((2.0 * (n / (k / Math.PI))));
}
def code(k, n): return math.sqrt((2.0 * (n / (k / math.pi))))
function code(k, n) return sqrt(Float64(2.0 * Float64(n / Float64(k / pi)))) end
function tmp = code(k, n) tmp = sqrt((2.0 * (n / (k / pi)))); end
code[k_, n_] := N[Sqrt[N[(2.0 * N[(n / N[(k / Pi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{2 \cdot \frac{n}{\frac{k}{\pi}}}
\end{array}
Initial program 99.1%
Taylor expanded in k around 0 40.8%
*-commutative40.8%
associate-/l*40.8%
Simplified40.8%
sqrt-unprod41.0%
clear-num40.9%
un-div-inv41.0%
Applied egg-rr41.0%
(FPCore (k n) :precision binary64 (sqrt (* 2.0 (* PI (/ n k)))))
double code(double k, double n) {
return sqrt((2.0 * (((double) M_PI) * (n / k))));
}
public static double code(double k, double n) {
return Math.sqrt((2.0 * (Math.PI * (n / k))));
}
def code(k, n): return math.sqrt((2.0 * (math.pi * (n / k))))
function code(k, n) return sqrt(Float64(2.0 * Float64(pi * Float64(n / k)))) end
function tmp = code(k, n) tmp = sqrt((2.0 * (pi * (n / k)))); end
code[k_, n_] := N[Sqrt[N[(2.0 * N[(Pi * N[(n / k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}
\\
\sqrt{2 \cdot \left(\pi \cdot \frac{n}{k}\right)}
\end{array}
Initial program 99.1%
Taylor expanded in k around 0 40.8%
*-commutative40.8%
associate-/l*40.8%
Simplified40.8%
sqrt-unprod41.0%
clear-num40.9%
un-div-inv41.0%
Applied egg-rr41.0%
associate-/r/40.9%
Applied egg-rr40.9%
Final simplification40.9%
herbie shell --seed 2024165
(FPCore (k n)
:name "Migdal et al, Equation (51)"
:precision binary64
(* (/ 1.0 (sqrt k)) (pow (* (* 2.0 PI) n) (/ (- 1.0 k) 2.0))))